In the last decade, there has been a growing body of literature addressing the utilization of
complex network methods for the characterization of dynamical systems based on time …

There is nowadays a constant flux of data being generated and collected in all types of real
world systems. These data sets are often indexed by time, space, or both requiring …

A growing number of algorithms have been proposed to map a scalar time series into
ordinal partition transition networks. However, most observable phenomena in the empirical …

The spatio-temporal features of the velocity field of a fully-developed turbulent channel flow
are investigated through the natural visibility graph (NVG) method, which is able to fully map …

Complex networks are widely used in modeling complex system. How to aggregate data in
complex systems is still an open issue. In this paper, an ordered visibility graph average …

The limited penetrable horizontal visibility algorithm is an analysis tool that maps time series
into complex networks and is a further development of the horizontal visibility algorithm. This …

There exist rich patterns in nonlinear dynamical processes, but they merge into averages in
traditional statistics-based time series analysis. Herein the multi-scale transition matrix is …

The volatility clustering has critical implications in financial risk management. This paper
aims to analyze the existence and cause of volatility clustering in financial time-series using …

A sentence is the natural unit of language. Patterns embedded in series of sentences can be
used to model the formation and evolution of languages, and to solve practical problems …

Understanding the dynamic evolution and fluctuation characteristics of air traffic flow volume
time series is the basis for designing effective air traffic flow management measures and …